The biology and management of systemic anaplastic large cell lymphoma
Bibliographic record
Abstract
Systemic anaplastic large cell lymphoma (ALCL) is an aggressive CD30(+) non-Hodgkin lymphoma. Anaplastic lymphoma kinase-positive (ALK+) ALCL is associated with the NPM-ALK t(2;5) translocation, which is highly correlated with the identification of the ALK protein by immunohistochemistry. ALK+ ALCL typically occurs in younger patients and has a more favorable prognosis with 5-year survival rates of 70% to 90% in comparison with 40% to 60% for ALK-negative (ALK-) ALCL. Studies support young age as a strong component of the favorable prognosis of ALK+ ALCL. Until recently, no recurrent translocations were identified in ALK- ALCL. However, emerging data now highlight that ALK- ALCL is genetically and clinically heterogeneous with a subset having either a DUSP22 translocation and a survival rate similar to ALK+ ALCL or a less common P63 translocation, the latter associated with an aggressive course. Anthracycline-based regimens such as cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) remain the standard first-line treatment choice for systemic ALCL, but in many patients with ALK- ALCL, it is ineffective, and thus it is often followed by consolidative autologous stem cell transplantation. However, selection of appropriate patients for intensified therapy remains challenging, particularly in light of genetic and clinical heterogeneity in addition to the emergence of new, effective therapies. The antibody drug conjugate brentuximab vedotin is associated with a high response rate (86%) and durable remissions in relapsed/refractory ALCL and is under investigation in the first-line setting. In the future, combining clinical and genetic biomarkers may aid in risk stratification and help guide initial patient management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".